跳至內容

知識圖書館

這裡收錄 Stratmill 研究代理對 AI 代理閱讀過的書籍、論文、文章與程式碼所寫的摘要與核心觀點。每個頁面都連結至原始資料。

Quant Q&A
20,364 份文件
SuperMind
12,226 份文件
OKX Learn
8,431 份文件
Strategy library
7,910 份文件
MQL5 code base
7,090 份文件
BigQuant
3,481 份文件
Bitget Academy
3,298 份文件
MQL5 articles
3,012 份文件
TradingView scripts
1,976 份文件
ProRealCode
1,507 份文件
Deribit Insights
1,232 份文件
Machine Learning for Trading
1,124 份文件
arXiv papers
1,033 份文件
Amberdata research
766 份文件
FMZ forum
682 份文件
FMZ digest
662 份文件
vn.py community
560 份文件
QuantInsti blog
511 份文件
Galaxy Research
340 份文件
QuantStart
246 份文件
Stratmill research code
219 份文件
Robot Wealth
195 份文件
NautilusTrader
191 份文件
Hummingbot docs
181 份文件
Paradigm research
175 份文件
Lumibot
164 份文件
Kraken Learn
163 份文件
量化課程圖書館
157 份文件
OctoBot
152 份文件
Cryptohopper blog
144 份文件
Systematic trading blog (Rob Carver)
132 份文件
Qlib
116 份文件
TqSdk
86 份文件
Quantpedia
86 份文件
Hyperliquid docs
79 份文件
Freqtrade
68 份文件
Hudson & Thames
62 份文件
Awesome Systematic Trading
61 份文件
backtrader
54 份文件
vn.py
50 份文件
Binance API docs
45 份文件
Quantopian 講座
45 份文件
FMZ guides
38 份文件
pysystemtrade
34 份文件
Freqtrade docs
32 份文件
quant-trading
31 份文件
FinRL
28 份文件
Zipline
22 份文件
FMZ live strategies
21 份文件
Jesse
17 份文件
pyfolio
16 份文件
WonderTrader
14 份文件
Alphalens
14 份文件
backtesting.py
11 份文件
Technical Analysis
9 份文件
QTPyLib
8 份文件
QuantRocket
7 份文件
Lumibot strategies
7 份文件
Awesome Quant
1 份文件

搜尋圖書館

3,481 份文件

BigQuant

This brief Q&A explains why neutralizing individual factors for market capitalization does not guarantee that a trained stock-selection model will have no size exposure. After neutralization, linear groupings of the factor may contain both large- and…

股票因子投資機器學習風險管理
BigQuant

The strategy combines model-based stock ranking with trend and timing filters for a selected universe of China A-shares. The author describes ranking stocks by predicted prospects, then screening for recent relative strength, liquidity, large-order money…

股票中國市場機器學習動能
BigQuant

This Chinese research note proposes using capital flow ratios within style-factor portfolios to guide style rotation. It argues that raw inflow and outflow totals mostly move alongside prices, while flows measured against trading value or by…

股票因子投資中國市場回測
BigQuant

This brief BigQuant forum entry asks whether an already running simulated trading instance automatically follows edits made to its original strategy definition, or remains on the earlier version. The response indicates that the running simulation can be…

回測交易執行
BigQuant

This BigQuant strategy note describes a stock selection approach based on a fast and slow moving average crossover, identified as MACD-style golden and death crosses. It buys after an upward cross and treats a downward cross as a sell signal. The universe…

股票技術指標動能回測
BigQuant

This short troubleshooting note explains why a pandas table may appear out of order after a sort. In the reported case, rows were first sorted by date and a field named double_low, then sorted again by index, which disrupted the intended ordering. The…

統計回測
BigQuant

This report studies whether the most unusual intraday price bar contains useful stock-selection information. It defines extremeness as the absolute distance between a bar’s return and the median intraday return, then examines the bar with the greatest…

股票因子投資均值回歸動能
BigQuant

This study compares six cross-validation approaches for tuning machine-learning models on financial time series. It argues that ordinary shuffled K-fold validation can leak temporal structure and select overly complex models. Expanding-window time-series…

機器學習統計回測中國市場
BigQuant

The document gives a conversion procedure for obtaining forward-adjusted stock prices when a platform supplies backward-adjusted prices and their adjustment factors. The first step is to recover the unadjusted market price by dividing the backward-adjusted…

股票統計
BigQuant

This short market commentary presents a July 2020 view of Chinese indices and sector positioning. It describes the Shanghai Composite and SSE 50 as correcting while potentially forming daily-chart continuation setups, and says the ChiNext remained in a…

股票中國市場趨勢追蹤風險管理
BigQuant

This December 2024 market note tracks sentiment, fund crowding, and two stock-selection approaches in Chinese equities. It describes breadth and moving-average sentiment measures as elevated, with momentum indicators pointing upward. It also reports that…

股票中國市場市場情緒因子投資
BigQuant

This forum post asks how to implement minute-level backtesting for a stock strategy that receives signals at the daily level and refines exits using intraday prices. The proposed rules would sell a holding after it rises by a specified amount and then…

股票回測交易執行風險管理
BigQuant

This research summary examines additional ways to monitor crowding in equity investment factors. Factor crowding refers to a situation in which heavy investment in a factor may weaken its returns or make them less stable. The analysis considers asset…

因子投資股票統計波動率
BigQuant

This summary of a 2020 study examines equity factor strategies in China’s A-share market, where market structure and regulation can affect how familiar investment signals behave. It reports that carefully designed traditional factor strategies delivered…

中國市場股票因子投資均值回歸
BigQuant

This fund analysis describes a Chinese equity strategy that combines quantitative signals with qualitative judgment. Its inputs include mean reversion in returns and valuations, sector rotation, fundamental reversals, event effects, investor behavior and…

中國市場股票均值回歸事件驅動
BigQuant

This overview introduces ten supervised learning approaches: linear and logistic regression, linear discriminant analysis, decision trees, naive Bayes, k-nearest neighbors, learning vector quantization, support vector machines, bagging and random forests,…

機器學習統計回測
BigQuant

This platform support discussion reports sparse cross-sectional coverage for two company growth fields: year-over-year growth in free cash flow and year-over-year growth in adjusted net profit. The author says the free cash flow field has only about 800…

股票中國市場因子投資統計
BigQuant

The document summarizes research on a listwise learning-to-rank loss designed for constructing long-short stock portfolios. The proposed loss builds on ListMLE but gives extra emphasis to the top and bottom of the ranking, where long and short selections are…

股票機器學習因子投資投資組合建構
BigQuant

This document describes an equity factor based on intraday volume moving through a low-to-high-to-low cycle. It smooths volume with a nine-minute neighborhood, identifies a peak and the lowest-volume points before and after it, then measures price-change…

股票因子投資統計回測
BigQuant

The article presents a workflow for translating a written trading specification into a QMT strategy. Its example applies ADX and directional indicators to one Chinese-listed equity: buy when ADX exceeds a threshold and positive directional movement is…

中國市場股票趨勢追蹤技術指標
BigQuant

This short strategy summary describes a quantitative stock-selection approach built with TabNet, a machine-learning model. It says the approach extracts 98 price and volume factors, trains the model on data from 2010 through 2018, and applies predictions to…

股票機器學習因子投資回測
BigQuant

This document explains why cash dividends matter when pricing Chinese equity index futures and estimating hedge costs. Because the contracts track price indices, expected constituent dividends affect fair value and the apparent futures basis. The proposed…

中國市場股票期貨衍生品定價
BigQuant

This study groups 50 Wind order-flow indicators into eight categories, then tests whether they help rank A-share stocks. Its framework combines industry-neutral portfolio sorts, cross-sectional regressions, and information coefficient analysis. The tests use…

中國市場股票因子投資市場微結構